There is a gap in knowledge regarding the specific etiologies for most cardiovascular malformations (CVMs). This gap represents a significant problem, because until it is solved, the underlying molecular mechanisms will be largely impenetrable. Our long term goal is to better understand the underlying genetic causes and molecular mechanisms leading to CVMs. The overall objective of this R21 application is to discover the genetic variation leading to a subgroup of CVMs, the left ventricular outflow tract (LVOT) malformations that includes aortic valve stenosis, coarctation of the aorta, and hypoplastic left heart syndrome. There is a large genetic component to these malformations, but few susceptibility genes have been identified. The central hypothesis is disease causing genes can be identified by highly selective genome-wide approaches, using families exhibiting Mendelian inheritance patterns for LVOT malformations. The rationale for the proposed research is that identifying the genetic causes of LVOT malformations has the potential to provide better risk counseling for a group of malformations that contribute to a large proportion of infant mortality due to birth defects. Guided by recent literature supporting this premise and possession of a unique cohort of families, the central hypothesis will be tested by pursuing a single specific aim to use genome partitioning capture technology for the exons of all known human genes followed by massively parallel sequencing of the captured targets. This will be applied to affected individuals from four pedigrees exhibiting an autosomal dominant inheritance pattern. Unlikely disease causing variants will be filtered out, based on existing variant databases and publically available personal genome sequence data. Bioinformatics will be used (predicted mutation effect, gene expression data, etc.) to identify the causal variant. Variants will be confirmed by Sanger sequencing and their functional effects investigated by expression assays. A larger cohort will then be screened for mutations in the identified genes. This approach is innovative. It will employ new technology to rapidly identify the causative gene in multiplex families, by-passing previous methods of genome wide linkage analysis, fine mapping, and candidate gene selection, creating a paradigm shift in the approach to gene mapping. In addition, unique methods have been developed to filter the large amount of expected data and identify the likely causal variant. The proposed research is significant because it is expected to vertically advance the field by identifying the first causal genes for LVOT malformations. The natural progression of this work will lead to an R01 application to investigate the molecular mechanisms of the variants identified. In the current era of fetal diagnosis and intervention, as well as the understanding that many CVMs are inherited, this knowledge can potentially be used to provide better family risk counseling, novel preventive measures, early in utero diagnosis, and targeted therapies.